How can traditional statistical relationships be redefined through citizen to government partnerships?

Article type: Research Article

Authors: Carranza-Torres, Javier Andrés

Affiliations: Director of GeoCensos Foundation, Programme Committee Member at World Data Forum, Calle 67 #59-46, Bogotá, Colombia | Tel./Fax: +57 1 4595159; Mobile/Whatsapp: +52 1 722 834 9596; E-mail: [email protected]

Correspondence: [*] Corresponding author: Director of GeoCensos Foundation, Programme Committee Member at World Data Forum, Calle 67 #59-46, Bogotá, Colombia. Tel./Fax: +57 1 4595159; Mobile/Whatsapp: +52 1 722 834 9596; E-mail: [email protected].

Abstract: The post-2015 Development Agenda proposes to produce much more statistics and data than currently available in the official arena through advanced methods and innovative partnerships. By associating governments and data producers of all kinds it aims to monitor the Sustainable Development Goals (SDGs). The objective of this paper is to explore and analyse one of the 2030 Agenda greatest challenges, i.e. to redefine traditional statistical relationships and processes to associate citizenry as an active stakeholder in the monitoring of SDGs. It proposes innovative ideas linking citizen-to-government and government-to-citizen data partnerships (C2G dp and G2C dp) to the SDG requirements. The paper portrays and analyses the benefits for parties of alternative projects from Uganda, Canada and Uruguay. The C2G dp Stats Up program is featured as an additional case study, describing its achievements and shortcomings. This contribution constitutes a valuable co-creation case to fill the gap of lack of partnering skills. In sum, the paper presents the added value of a constructive socio-technical approach to SDG 17. Final conclusions propose a roadmap to support the work of National Statistical Offices to address complex challenges to walk the talk of the 2030 Agenda harnessing the crucial role of civil society in their plans.

Keywords: Sustainable development goals, data partnerships, official statistics, third party data, civil society

DOI: 10.3233/SJI-190578

Journal: Statistical Journal of the IAOS, vol. 37, no. 1, pp. 229-243, 2021